How scalable is Stacker?

Is stacker more of a solution for an MVP or can it scale with a company as the data size grows? Really trying to understand if there are performance issues with scale or not

Hi @alexverstappen, the answer depends on quite a lot of factors, including your definition of scale. A big question is how many records you’d actively need access to.

It often also comes down to how complex the app you build is. For instance - if you had an app that displays record data in a fairly straightforward way without referencing lots of related records, or using any scripts, you’d be able to get better performance as the app grew than if you had a more complex app.

Regarding the scalability of Stacker I’m not 100% sure, but my sense is that you’d want a properly engineered product and backend for large scale applications. But the scalability of the underlying data sources (e.g. Airtable, Google Sheets, etc.) is definitely limited (likely more so than Stacker itself).

Related records inherently happens and is a necessity as your data grows. Needing a database like Postgres, MongoDB, or Snowflake can handle these.

If Airtable or Google Sheets is what’s limiting you then here’s what you could do (based on other forum questions and some practices in the company I’m at) I’d recommend using an ETL service like Airbyte ( to get your data into a true database. If you want to keep using Airtable or Google Sheets but have that data in a more scalable system, you could use Bracket ( to send the data to a database but keep using Airtable / Google Sheets as a UI for your database.
You could try using Zapier, Integromat, or Make as well but it may also run into scalability issues for this kind of use case.

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Really good points @Zwolletrust - I’ve heard of a few people who use a true database like Postgres to store all their information then use a service like Bracket or to bring a subset of that database that they need easy access to into GSheets or Airtable (then use Stacker to let users access that data :slight_smile: )